Measuring individual inbreeding in the age of genomics: marker-based measures are better than pedigrees

Abstract

Inbreeding (mating between relatives) can dramatically reduce the fitness of offspring by causing parts of the genome to be identical by descent. Thus, measuring individual inbreeding is crucial for ecology, evolution and conservation biology. We used computer simulations to test whether the realized proportion of the genome that is identical by descent (IBDG) is predicted better by the pedigree inbreeding coefficient (FP) or by genomic (marker-based) measures of inbreeding. Genomic estimators of IBDG included the increase in individual homozygosity relative to mean Hardy-Weinberg expected homozygosity (FH), and two measures (FROH and FE) that use mapped genetic markers to estimate IBDG. IBDG was more strongly correlated with FH, FE and FROH than with FP across a broad range of simulated scenarios when thousands of SNPs were used. For example, IBDG was more strongly correlated with FROH, FH and FE (estimated with ⩾10 000 SNPs) than with FP (estimated with 20 generations of complete pedigree) in populations with a recent reduction in the effective populations size (from Ne=500 to Ne=75). FROH, FH and FE generally explained >90% of the variance in IBDG (among individuals) when 35 K or more SNPs were used. FP explained <80% of the variation in IBDG on average in all simulated scenarios, even when pedigrees included 20 generations. Our results demonstrate that IBDG can be more precisely estimated with large numbers of genetic markers than with pedigrees. We encourage researchers to adopt genomic marker-based measures of IBDG as thousands of loci can now be genotyped in any species.

Figure 1

The distribution of IBD_G among 5000 simulated offspring of full siblings with 20 chromosomes of equal length, and 800 cM (upper panel) or 3600 cM (lower panel) genomes.

Figure 2

Barplots of the mean r² (±1 s.d. among 20 simulated populations) from regressions of F_P, F_E, F_H and F_ROH versus IBD_G. The data shown are from 20 partially isolated populations (top row) and also 20 populations with recently reduced N_e (bottom row) and 3600 cM genomes. Dashed lines at r²=0.9 are to aid comparison of r² for F_P, F_H, F_E and F_ROH.

Figure 3

Barplots of the mean bias of F_P, F_H, F_E and F_ROH (±1 s.d. among 20 simulated populations). Bias was measured as the mean error (F_P, F_H, F_E or F_ROH minus IBD_G) across all individuals in each simulated population. The data shown are from 20 partially isolated populations (top row) and 20 populations with recently reduced N_e (bottom row) and 3600 cM genomes.

Figure 4

F_P (a), F_H (b), F_ROH (c) and F_E (d) versus IBD_G in a population with recently reduced N_e and 3600 cM genomes. F_P was estimated with five generations. F_H, F_E and F_ROH were estimated with 25 K SNPs. The dashed lines have intercept of zero and slope of one. Points below the lines represent underestimates of IBD_G.

Figure 5

Ratios of the standard deviation of F_P, F_E, F_H and F_ROH to the standard deviation of IBD_G. The data shown are from partially isolated populations (top row) and populations with recently reduced N_e (bottom row) and 3600 cM genomes. The dashed lines represent a ratio of 1. Bars extending above and below the line represent over- and underestimates, respectively, of the difference in IBD_G among individuals.